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9 th Washington group, Dar Es Salaam October 2009

9 th Washington group, Dar Es Salaam October 2009. Population estimates of disability The impact of including or not the population living in institutions Emmanuelle Cambois (INED, France) For the EHLEIS program.

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9 th Washington group, Dar Es Salaam October 2009

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  1. 9th Washington group, Dar Es Salaam October 2009 Population estimates of disability The impact of including or not the population living in institutions Emmanuelle Cambois (INED, France) For the EHLEIS program

  2. Context: Are disability statistics data representative of the whole population?The health of the population is measured by health surveys that are most of the time onlybased on household population: difficulty to organise a survey in institution, various situation worldwide.Shall we develop surveys in institutions to be able to compare? % Disability, activity limitations, functional problems… ? Household population Outside Households

  3. How do we deal with this so far? 1> Proposing an aggregate health indicator, the disability free life expectancy, Sullivan was suggesting considering that living in institution was an expression of disability and recommended considering the prevalence of disability as 100% in institutions (Sullivan, 1971). 2> Eurostat calculation of Healthy Life years is only based on HH prevalence, tacitly assuming that the same prevalence can be observed in and outside HH

  4. Medical, nursing, disability Collective HH How relevant are these assumptions 2. A part of the population outside HH lives in collective HH and a part lives in nursing or health care institution.Differences btw countries? % Disability, activity limitations, functional problems… ? Household population Outside Households

  5. Context3. To what extent the prevalence differs from the HHpopulation prevalence? ? ? Medical, nursing, disability Collective HH % Disability, activity limitations, functional problems… Household population Outside Households

  6. Assumptions > Proposing an aggregate health indicator, the disability free life expectancy, Sullivan was suggesting considering that living in institution was an expression of disability and recommended considering the prevalence of disability as 100% in institutions (Sullivan, 1971). While this can be reasonable assumption for nursing homes and long term hospital services, this can be consider as a quite strong assumption for other types of collective, while distinction can not be all the time be made with regular statistics > Eurostat calculation of Healthy Life years is only based on HH prevalence, tacitly assuming that the same prevalence can be observed in and outside HH. This assumption might be optimistic considering that part of the population is actually in poorest health than in HH, but it depends on the % of such institutions within the population living outside HH.

  7. Questions What is the impact of these assumptions on estimates? Is it worth for international comparison to address the issue of survey in institutions? • Looking at the European populations living outside HH • What is the distribution between HH and population outside HH across Europe? • Whatis the distribution of the care institutions in the population outside HH (3 countries)? • The impact on the level of prevalence of disability and on healthy life years? • - considering Sullivan vs. Eurostat on outside HH population • - considering Sullivan + + whenli;ited to the care related institutions • Whatis the real prevalence of disability in institutions; in between the twoassumptions

  8. 1. The European populations living outside HH • What is the distribution between HH population and population outside HH across Europe? (example with 13 countries) • From 3.5% in Greece to lessthan 1% in Italy or Cyprus • Large variation in the type of population regarding % in age groups

  9. 1. The European populations living outside HH • What is the distribution of the institutions/collective HH in the population outside HH across Europe? Example with France, Italy, The Netherlands

  10. 1. The European populations living outside HH • Gap on the Eurostat estimates vs Sullivan with the care related institutions? % living outside HH and % in nursing/care institutions

  11. 2. Impact of the assumptions on the prevalence of « Activity limitation »

  12. 2. Effect on the prevalance of « Activity limitation » The number of people with activity limitation in adult population + 4,3% + 1,4% + 1,2%

  13. 2. Effect on HLY calculations At age 65

  14. 2. Effect on HLY calculations At birth, gap from 30 mth (Gr men) to 2.9 mth (Lth/Cy women) At 65, gap from 8 mth (Ir women) to <1 mth (Lth/Cy women

  15. 2. Effect on HLY calculations Number of years differences between HLY and DFLE in The Netherlands • High institutionalization rate, due to high rate for elderly • Up to 1 yeardifferenceaccording to the assumption • Reduced to lessthan 10 month if limiting to « care related institutions »

  16. 2. Effect on HYL calculations • Eurostat calculationsoverestimate the HLY to a differentextentfrom one country to anotherregarding Sullivan assumption • The gap reduces if consideringonly care related institutions • How reliablecouldbe Sullivan assumptioncompared to Eurostat? Whatcouldbe the gap in prevalence of GALI in institution vs. HH or vs. 100%?

  17. 3. Estimates based on comparable HH/Institutions survey In late 1990’s, HID is a HH/Institution based on the French health and disability survey:

  18. 3. Estimates based on comparable HH/Institutions survey 53,3 53,05 52,8

  19. 3. Estimates based on comparable HH/Institutions survey • For disability status with low prevalence (ADL), the difference btw HH and Inst are large but the total number of persons concerned is limited: the impact of both assumptions is larger than the confidence interval. Eurostat assumption diverges more than Sullivan, reach a 7 month of HLExp at age 20 • For disabilitystatuswithhighprevalence (commonwithage…), the differencebtw HH and Instprevalencereduceswithagewhile % living in institution increases. This inverted trends makes the impact of eitherassumptionsloweven if Sullivan iscloser to the observation. The differences are within the IC.

  20. Conclusion • Based only on HH information, population estimates are underestimating the prevalence of disability. The magnitude of the bias depending on the age patterns of living outside institution and type of disability under consideration. • Sullivan assumption seems more accurate but only when statistics allows to focus on health related institutions. • But, the variation of the % and type of institutions across Europe prevents from applying Sullivan assumption. • In any case, the reality is in between the two assumptions, giving the two limits of a range for the estimates • Such approach can be useful to avoid conducting worldwide surveys in institution to better estimate population disability prevalence

  21. The Netherlands 1. The European populations living outside HH • What is the distribution of the institutions/collective HH in the population outside HH across Europe? Example with France, Italy and the Netherlands

  22. 3. The calculations of HLY: Sullivan vs. Eurostat assumption At birth

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